# Technical Stack Evaluation

<div class="lore-card">
  <h3>Evaluation Approach</h3>
  <p>
    Technology decisions are made based on learning value, flexibility, and long-term scalability rather than short-term convenience.
  </p>
  <p>
    Each tool is evaluated in context of how it supports the system's evolution.
  </p>
</div>

## 🎯 Selection Criteria
To support a public-facing, scalable gaming utility, the stack was evaluated against four core pillars:
1. **Real-Time Latency:** Must support <100ms sync.
2. **Cross-Platform Delivery:** Native performance on both mobile and web.
3. **AI Extensibility:** Ease of integration with LLM APIs (Gemini/OpenAI).
4. **Economic Scalability:** Low per-user overhead.

## Current Prototype Recommendation: MIT App Inventor
Chosen for:
- zero-cost learning environment
- fast iteration
- beginner-friendly logic building
- hands-on understanding of app structure and state

## Future Rebuild Candidates
### Option A: FlutterFlow + Supabase
Pros:
- closer to intended app architecture
- less Firebase billing pressure
- useful for future migration

### Option B: FlutterFlow + Firebase
Pros:
- strong real-time features
- native FlutterFlow support
Cons:
- billing limitations for current stage

## Decision
Use MIT App Inventor for Phase 1 learning and prototyping.
Revisit FlutterFlow + Supabase/Firebase after core workflows are proven.

## 🏆 Final Recommendation: FlutterFlow + Firebase
After comparing **Bubble.io** (Rapid Prototyping) and **Supabase/Next.js** (Custom Scale), the **FlutterFlow + Firebase** stack was selected for the final build.

* **Native Performance:** Unlike web-wrapped builders, FlutterFlow provides high-performance native UX essential for live table play.
* **Firestore Real-Time DB:** Native support for the "Live HUD" features without requiring complex custom WebSocket management.
* **Deployment Agility:** Faster speed-to-market for a high-fidelity MVP.